Correlation Between Gmo Alternative and Loomis Sayles
Can any of the company-specific risk be diversified away by investing in both Gmo Alternative and Loomis Sayles at the same time? Although using a correlation coefficient on its own may not help to predict future stock returns, this module helps to understand the diversifiable risk of combining Gmo Alternative and Loomis Sayles into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Gmo Alternative Allocation and Loomis Sayles High, you can compare the effects of market volatilities on Gmo Alternative and Loomis Sayles and check how they will diversify away market risk if combined in the same portfolio for a given time horizon. You can also utilize pair trading strategies of matching a long position in Gmo Alternative with a short position of Loomis Sayles. Check out your portfolio center. Please also check ongoing floating volatility patterns of Gmo Alternative and Loomis Sayles.
Diversification Opportunities for Gmo Alternative and Loomis Sayles
-0.58 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Gmo and Loomis is -0.58. Overlapping area represents the amount of risk that can be diversified away by holding Gmo Alternative Allocation and Loomis Sayles High in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Loomis Sayles High and Gmo Alternative is a relative statistical measure of the degree to which these equity instruments tend to move together. The correlation coefficient measures the extent to which returns on Gmo Alternative Allocation are associated (or correlated) with Loomis Sayles. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Loomis Sayles High has no effect on the direction of Gmo Alternative i.e., Gmo Alternative and Loomis Sayles go up and down completely randomly.
Pair Corralation between Gmo Alternative and Loomis Sayles
Assuming the 90 days horizon Gmo Alternative is expected to generate 4.86 times less return on investment than Loomis Sayles. In addition to that, Gmo Alternative is 1.04 times more volatile than Loomis Sayles High. It trades about 0.03 of its total potential returns per unit of risk. Loomis Sayles High is currently generating about 0.13 per unit of volatility. If you would invest 747.00 in Loomis Sayles High on August 26, 2024 and sell it today you would earn a total of 153.00 from holding Loomis Sayles High or generate 20.48% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Gmo Alternative Allocation vs. Loomis Sayles High
Performance |
Timeline |
Gmo Alternative Allo |
Loomis Sayles High |
Gmo Alternative and Loomis Sayles Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Gmo Alternative and Loomis Sayles
The main advantage of trading using opposite Gmo Alternative and Loomis Sayles positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Gmo Alternative position performs unexpectedly, Loomis Sayles can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Loomis Sayles will offset losses from the drop in Loomis Sayles' long position.Gmo Alternative vs. Firsthand Technology Opportunities | Gmo Alternative vs. Columbia Global Technology | Gmo Alternative vs. Allianzgi Technology Fund | Gmo Alternative vs. Dreyfus Technology Growth |
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Check out your portfolio center.Note that this page's information should be used as a complementary analysis to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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